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Abstract #3186

Nonlocal multispectral image filtering to improve determination of cerebral blood flow from pseudo-continuous arterial spin labeling imaging

Mustapha Bouhrara1, Diana Y. Lee1, Abinand C. Rejimon1, and Richard G. Spencer1

1National Institute on Aging, National Institutes of Health, Baltimore, MD, United States

Changes in the cerebral blood flow (CBF), measured using arterial spin labeling (ASL), are an emerging biomarker for normal aging, Alzheimer's disease, and other neurodegenerative conditions. However, ASL signal-to-noise ratio (SNR) is inherently low, diminishing the quality of CBF determination. While attempts have been made to improve SNR in ASL images using post-processing filters, performance is limited and several user-defined parameters are required adding further complexity in implementation. Here, we introduce a simple, novel filtering algorithm and demonstrate its potential to enhance the quality of CBF mapping.

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